IEEE

Triple Dynamic Graph Convolutional Recurrent Network for Traffic Prediction

Abstract: Effective traffic prediction is a critical component of traffic management, especially long-term traffic prediction, as it holds significance for urban traffic planning, traffic warning, ...
GitHub

Pull requests: Gabriele-Immordino/Spatio-temporal-Graph-Convolutional-Autoencoder-for-Transonic-Wing-Pressure-Distribution-Forecasting

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.
Frontiers

Deep learning-based object detection for environmental monitoring using big data

Introduction: Recent advances in artificial intelligence have transformed the way we analyze complex environmental data. However, high-dimensionality, spatiotemporal variability, and heterogeneous ...
Frontiers

Association prediction of lncRNAs and diseases using multiview graph convolution neural network

1 College of Computer Science and Engineering, Changsha University, Changsha, Hunan, China 2 Department of Information and Computing Science, College of Mathematics, Changsha University, Changsha, ...
Scientific Research Publishing

Mao, X.J., Shen, C. and Yang, Y.B. (2016) Image Restoration Using Convolutional Auto-Encoders with Symmetric Skip Connections.

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...
Scientific Research Publishing

Phan, A.V., Nguyen, M.L., Nguyen, Y.L.H. and Bui, L.T. (2018) DGCNN: A Convolutional Neural Network over Large-Scale Labeled Graphs. Neural Networks, 108, 533-543.

ABSTRACT: Point cloud-based 3D object detection is a key technology in autonomous driving and mobile robot perception systems. However, the sparsity and irregularity of point cloud data result in poor ...
IEEE

Auto-encoder based Graph Convolutional Networks for Online Financial Anti-fraud

Abstract: Many practical problems can be formulated as graph-based semi-supervised classification problems. For example, online finance anti-fraud. Recently, many researchers attempt using deep ...